Development and validation of a nomogram model for early postoperative hyperlactatemia in patients undergoing cardiac surgery

BACKGROUND: Postoperative hyperlactatemia (POHL) is common in patients undergoing cardiac surgery, associated with adverse outcomes. The aim of this study was to identify predictors for POHL after cardiac surgery and to develop and validate a predictive model. METHODS: Adult patients who underwent open heart surgery at our institution between 2016 and 2019 were retrospectively included. The patients were randomly divided into training and validation groups at a 2:1 ratio. Multivariate logistic regression was performed to identify independent predictors for POHL in the training set. A nomogram was then constructed and was validated in the validation set. RESULTS: 2.1%, P<0.001). Age, white blood cell (WBC) count, left ventricular ejection fraction, renal insufficiency, cardiac surgery history, red blood cell (RBC) transfusion, and cardiopulmonary bypass (CPB) time were identified as independent risk factors. The nomogram based on these predictors indicated good discrimination in both the training (c-index: 0.787) and validation (c-index: 0.820) sets. The calibration was reasonable by both visual inspection and goodness-of-fit test. The decision and clinical impact curves demonstrated good clinical utility. CONCLUSIONS: We identified 7 independent risk factors and derived a prediction model for POHL in patients undergoing cardiac surgery. The model may contribute significantly to early risk assessment and clinical intervention.